scholarly journals Anatomists Assemble! Integrating superheroes into the anatomy and physiology classroom

2021 ◽  
Vol 45 (3) ◽  
pp. 511-517
Author(s):  
Jeremy J. Grachan ◽  
Melissa M. Quinn
Keyword(s):  
Popular Culture ◽  
Sexual Orientation ◽  
Real World ◽  
Real Life ◽  
Clinical Correlates ◽  
Anatomy And Physiology ◽  
Personal Connections ◽  
Course Material ◽  
Secret Identities ◽  
Health Field

Anatomy and physiology courses are sometimes seen as difficult, which can lead to a lack of motivation in students to learn and engage in the course material. Students may also see the material as “dry,” have issues forming personal connections, or struggle to connect the content to the real world. These issues may lead to students not performing well in the course or feeling that the health field is not ideal for them. Popular culture, especially mainstream superheroes, can serve as an option for mending these gaps by being a gateway to connecting to many students’ lives. Superheroes can be integrated into the classroom through relevant, creative, and unique examples that include clinical correlates, modern scientific innovations, and some real-life “supers” living among us. Real anatomy and physiology can still be taught and explained through discussing these “incredible” examples and also present an opportunity for students to be creative in generating their own anatomical and physiological explanations for various superpowers. Superheroes also help open the classroom up to being a place of acceptance, primarily through their secret identities, which cover a broad range of idols that students can look up to, whether it is their career or based on a character’s race or sexual orientation. Professors can become the superhero in their classroom and help students become more engaged and interested in the material.

Neuropsychology in the Real World

2014 ◽  
Vol 25 (4) ◽  
pp. 233-238 ◽  
Author(s):  
Martin Peper ◽  
Simone N. Loeffler
Keyword(s):  
Neuropsychological Assessment ◽  
Real World ◽  
Ecological Validity ◽  
Real Life ◽  
Emotional States ◽  
Context Sensitive ◽  
Traditional Assessment ◽  
Life Data ◽  
Real Life Data ◽  
Assessment And Treatment

Current ambulatory technologies are highly relevant for neuropsychological assessment and treatment as they provide a gateway to real life data. Ambulatory assessment of cognitive complaints, skills and emotional states in natural contexts provides information that has a greater ecological validity than traditional assessment approaches. This issue presents an overview of current technological and methodological innovations, opportunities, problems and limitations of these methods designed for the context-sensitive measurement of cognitive, emotional and behavioral function. The usefulness of selected ambulatory approaches is demonstrated and their relevance for an ecologically valid neuropsychology is highlighted.

scholarly journals Dealing with multiple experts and non-stationarity in inverse reinforcement learning: an application to real-life problems

2021 ◽  
Author(s):  
Amarildo Likmeta ◽  
Alberto Maria Metelli ◽  
Giorgia Ramponi ◽  
Andrea Tirinzoni ◽  
Matteo Giuliani ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Real World ◽  
Real Life ◽  
User Preferences ◽  
Inverse Reinforcement Learning ◽  
Water Release ◽  
Reward Function ◽  
Model Free ◽  
Conflicting Objectives ◽  
Multiple Experts

AbstractIn real-world applications, inferring the intentions of expert agents (e.g., human operators) can be fundamental to understand how possibly conflicting objectives are managed, helping to interpret the demonstrated behavior. In this paper, we discuss how inverse reinforcement learning (IRL) can be employed to retrieve the reward function implicitly optimized by expert agents acting in real applications. Scaling IRL to real-world cases has proved challenging as typically only a fixed dataset of demonstrations is available and further interactions with the environment are not allowed. For this reason, we resort to a class of truly batch model-free IRL algorithms and we present three application scenarios: (1) the high-level decision-making problem in the highway driving scenario, and (2) inferring the user preferences in a social network (Twitter), and (3) the management of the water release in the Como Lake. For each of these scenarios, we provide formalization, experiments and a discussion to interpret the obtained results.

scholarly journals Improving the performance of a radio-frequency localization system in adverse outdoor applications

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Marcelo N. de Sousa ◽  
Ricardo Sant’Ana ◽  
Rigel P. Fernandes ◽  
Julio Cesar Duarte ◽  
José A. Apolinário ◽  
...  
Keyword(s):  
Random Forest ◽  
Ray Tracing ◽  
Real World ◽  
Practical Implication ◽  
Real Life ◽  
Simulated Data ◽  
Real Data ◽  
Gradient Boosting ◽  
Real World Data ◽  
Localization Accuracy

AbstractIn outdoor RF localization systems, particularly where line of sight can not be guaranteed or where multipath effects are severe, information about the terrain may improve the position estimate’s performance. Given the difficulties in obtaining real data, a ray-tracing fingerprint is a viable option. Nevertheless, although presenting good simulation results, the performance of systems trained with simulated features only suffer degradation when employed to process real-life data. This work intends to improve the localization accuracy when using ray-tracing fingerprints and a few field data obtained from an adverse environment where a large number of measurements is not an option. We employ a machine learning (ML) algorithm to explore the multipath information. We selected algorithms random forest and gradient boosting; both considered efficient tools in the literature. In a strict simulation scenario (simulated data for training, validating, and testing), we obtained the same good results found in the literature (error around 2 m). In a real-world system (simulated data for training, real data for validating and testing), both ML algorithms resulted in a mean positioning error around 100 ,m. We have also obtained experimental results for noisy (artificially added Gaussian noise) and mismatched (with a null subset of) features. From the simulations carried out in this work, our study revealed that enhancing the ML model with a few real-world data improves localization’s overall performance. From the machine ML algorithms employed herein, we also observed that, under noisy conditions, the random forest algorithm achieved a slightly better result than the gradient boosting algorithm. However, they achieved similar results in a mismatch experiment. This work’s practical implication is that multipath information, once rejected in old localization techniques, now represents a significant source of information whenever we have prior knowledge to train the ML algorithm.

scholarly journals An Adaptive Game-Based Learning Strategy for Children Road Safety Education and Practice in Virtual Space

Sensors ◽  
2021 ◽  
Vol 21 (11) ◽  
pp. 3661
Author(s):  
Noman Khan ◽  
Khan Muhammad ◽  
Tanveer Hussain ◽  
Mansoor Nasir ◽  
Muhammad Munsif ◽  
...  
Keyword(s):  
Real World ◽  
Road Safety ◽  
Learning Strategy ◽  
Real Life ◽  
Safety Training ◽  
Virtual Space ◽  
Safety Education ◽  
Average Output ◽  
Training Environment ◽  
The Road

Virtual reality (VR) has been widely used as a tool to assist people by letting them learn and simulate situations that are too dangerous and risky to practice in real life, and one of these is road safety training for children. Traditional video- and presentation-based road safety training has average output results as it lacks physical practice and the involvement of children during training, without any practical testing examination to check the learned abilities of a child before their exposure to real-world environments. Therefore, in this paper, we propose a 3D realistic open-ended VR and Kinect sensor-based training setup using the Unity game engine, wherein children are educated and involved in road safety exercises. The proposed system applies the concepts of VR in a game-like setting to let the children learn about traffic rules and practice them in their homes without any risk of being exposed to the outside environment. Thus, with our interactive and immersive training environment, we aim to minimize road accidents involving children and contribute to the generic domain of healthcare. Furthermore, the proposed framework evaluates the overall performance of the students in a virtual environment (VE) to develop their road-awareness skills. To ensure safety, the proposed system has an extra examination layer for children’s abilities evaluation, whereby a child is considered fit for real-world practice in cases where they fulfil certain criteria by achieving set scores. To show the robustness and stability of the proposed system, we conduct four types of subjective activities by involving a group of ten students with average grades in their classes. The experimental results show the positive effect of the proposed system in improving the road crossing behavior of the children.

Peer Sharing Facilitates the Effect of Inquiry-based Projects on Science Learning

2010 ◽  
Vol 72 (1) ◽  
pp. 24-29 ◽  
Author(s):  
Hui-Min Chung ◽  
Kristina Jackson Behan
Keyword(s):  
Popular Culture ◽  
Real World ◽  
Scientific Inquiry ◽  
Science Learning ◽  
Group Learning ◽  
Authentic Assessment ◽  
The Other ◽  
Learning Activity ◽  
Millennial Students ◽  
Inquiry Based Learning

Authentic assessment exercises are similar to real-world tasks that would be expected by a professional. An authentic assessment in combination with an inquiry-based learning activity enhances students' learning and rehearses them for their future roles, whether as scientists or as informed citizens. Over a period of 2 years, we experimented with two inquiry-based projects; one had traditional scientific inquiry characteristics, and the other used popular culture as the medium of inquiry. We found that activities that incorporated group learning motivated students and sharpened their abilities to apply and communicate their knowledge of science. We also discovered that incorporating popular culture provided ““Millennial”” students with a refreshing view of science learning and increased their appetites to explore and elaborate on science.

PALOMAGE, a French real-world cohort of elderly women beyond age 70 with advanced breast cancer receiving palbociclib: Baseline characteristics and safety evaluation.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1012-1012
Author(s):  
Philippe Caillet ◽  
Marina Pulido ◽  
Etienne Brain ◽  
Claire Falandry ◽  
Isabelle Desmoulins ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Advanced Breast Cancer ◽  
Real World ◽  
Older Patients ◽  
Systemic Treatment ◽  
Safety Data ◽  
Real Life ◽  
Advanced Breast ◽  
Baseline Characteristics ◽  
Grade 3

1012 Background: Advanced breast cancer (ABC) is common in older patients, resulting from the high incidence of breast cancer beyond age 70. This population is often limited in clinical trials. Endocrine therapy (ET) combined with a CDK4/6 inhibitor is the standard of care in ABC overexpressing hormonal receptors (HR+). Data specific to older patients are scarce in the literature, deserving further research. Methods: PALOMAGE is an ongoing French prospective study evaluating palbociclib (PAL) + ET in real life setting in women aged ≥70 with HR+ HER2- ABC, split in 2 cohorts: ET sensitive patients with no prior systemic treatment for ABC (cohort A), and ET resistant patients and/or with prior systemic treatment for ABC (cohort B). Data collected include clinical characteristics, quality of life (EORTC QLQ-C30 and ELD14) and geriatric description [G8 and Geriatric-COre DatasEt (G-CODE)]. This analysis reports on baseline characteristics and safety data for the whole population. Results: From 10/2018 to 10/2020, 400 and 407 patients were included in cohort A and B, respectively. The median age was 79 years (69-98), 15.1% with an age > 85. ECOG performance status (PS) was ≥2 in 17.9% patients, 68.3% had a G8 score ≤14 suggesting frailty, 32.1% had bone only metastasis, and 44% had visceral disease. 35.8% of patients in cohort B had no prior treatment for ABC. Safety data were available for 787 patients. The median follow-up was 6.7 months (IC95% = 6.1-7.6). At start of treatment, full dose of PAL (125 mg) was used in 76% of the patients: 62.6%, 68.7% and 71.6% of patients aged ≥ 80, those with ECOG PS ≥2 and those with a G8 score ≤14, respectively. In the safety population, 70% had ≥1 adverse event (AE), including 43.1% grade 3/4 AE, and 22.9% ≥ 1 serious AE. Most frequent AE reported were neutropenia (43.2%), anemia (17.5%), asthenia (16.3%) and thrombocytopenia (13.6%). Grade 3/4 neutropenia was observed in 32.3% of patients, with febrile neutropenia in 1.1%. Grade 3/4 AE PAL-related were reported in 40.1%, 31.4% of patients aged < 80, ≥80, respectively. Regarding PAL, 23.4% of patients had a dose reduction and 41.8% had a temporary or permanent discontinuation due to AE. Safety data were similar in both cohorts. Geriatric data and impact on safety will be presented. Conclusions: PALOMAGE is a unique large real-world cohort focusing on older patients treated with PAL in France. These preliminary data do not suggest any new safety signal, matching data derived from PALOMA trials. The occurrence of less grade3/4 AE related to PAL in patients aged 80 and beyond might reflect the 30% decrease of PAL dose upfront. Effectiveness analyses are eagerly awaited. Clinical trial information: EUPAS23012 .

scholarly journals Experimentally-induced and real-world acute anxiety have no effect on goal-directed behaviour

2019 ◽  
Author(s):  
CM Gillan ◽  
MM Vaghi ◽  
FH Hezemans ◽  
Grothe S van Ghesel ◽  
J Dafflon ◽  
...  
Keyword(s):  
Individual Differences ◽  
Anxiety Disorders ◽  
Healthy Volunteers ◽  
Real World ◽  
Real Life ◽  
Stressful Events ◽  
Panic Attacks ◽  
Healthy Individuals ◽  
Correlational Design ◽  
Acute Anxiety

AbstractCompulsivity is associated with failures in goal-directed control, an important cognitive faculty that protects against developing habits. But might this effect be explained by co-occurring anxiety? Previous studies have found goal-directed deficits in other anxiety disorders, and to some extent when healthy individuals are stressed, suggesting this is plausible. We carried out a causal test of this hypothesis in two experiments (between-subject N=88; within-subject N=50) that used the inhalation of hypercapnic gas (7.5% CO2) to induce an acute state of anxiety in healthy volunteers. In both experiments, we successfully induced anxiety, assessed physiologically and psychologically, but this did not affect goal-directed performance. In a third experiment (N=1413), we used a correlational design to test if real-life anxiety-provoking events (panic attacks, stressful events) impair goal-directed control. While small effects were observed, none survived controlling for individual differences in compulsivity. These data suggest that anxiety has no meaningful impact on goal-directed control.

scholarly journals From Literacy to Information Literacy: Reading for Understanding in the Real World

2021 ◽  
pp. 254-267
Author(s):  
John Royce
Keyword(s):  
Information Literacy ◽  
Real World ◽  
Real Life ◽  
The Internet ◽  
Good Readers ◽  
The Real ◽  
Life Problems ◽  
Complicated Process ◽  
Process Failure ◽  
Vital Component

Good readers evaluate as they go along, open to triggers and alarms which warn that something is not quite right, or that something has not been understood. Evaluation is a vital component of information literacy, a keystone for reading with understanding. It is also a complex, complicated process. Failure to evaluate well may prove expensive. The nature and amount of information on the Internet make evaluation skills ever more necessary. Looking at research studies in reading and in evaluation, real-life problems are suggested for teaching, modelling and discussion, to bring greater awareness to good, and to less good, readers.

scholarly journals Real-Life Continuous Flash Suppression - Rendering The Real World Unconscious Using Augmented Reality Goggles

2018 ◽  
Author(s):  
Uri Korisky ◽  
Rony Hirschhorn ◽  
Liad Mudrik
Keyword(s):  
Augmented Reality ◽  
Real World ◽  
Three Dimensional ◽  
Real Life ◽  
Continuous Flash Suppression ◽  
Future Studies ◽  
The Real ◽  
Dominant Eye ◽  
Novel Variant ◽  
Real Objects

Notice: a peer-reviewed version of this preprint has been published in Behavior Research Methods and is available freely at http://link.springer.com/article/10.3758/s13428-018-1162-0Continuous Flash Suppression (CFS) is a popular method for suppressing visual stimuli from awareness for relatively long periods. Thus far, it has only been used for suppressing two-dimensional images presented on-screen. We present a novel variant of CFS, termed ‘real-life CFS’, with which the actual immediate surroundings of an observer – including three-dimensional, real life objects – can be rendered unconscious. Real-life CFS uses augmented reality goggles to present subjects with CFS masks to their dominant eye, leaving their non-dominant eye exposed to the real world. In three experiments we demonstrate that real objects can indeed be suppressed from awareness using real-life CFS, and that duration suppression is comparable that obtained using the classic, on-screen CFS. We further provide an example for an experimental code, which can be modified for future studies using ‘real-life CFS’. This opens the gate for new questions in the study of consciousness and its functions.

scholarly journals A Novel Method based on Gaussianity and Sparsity for Signal Separation Algorithms

2017 ◽  
Vol 7 (4) ◽  
pp. 1906 ◽  
Author(s):  
Abouzid Houda ◽  
Chakkor Otman
Keyword(s):  
Independent Component Analysis ◽  
Blind Source Separation ◽  
Real World ◽  
Source Separation ◽  
Real Life ◽  
Signal Separation ◽  
Mixing Process ◽  
The Real ◽  
Input Signals ◽  
Novel Method

Blind source separation is a very known problem which refers to finding the original sources without the aid of information about the nature of the sources and the mixing process, to solve this kind of problem having only the mixtures, it is almost impossible , that why using some assumptions is needed in somehow according to the differents situations existing in the real world, for exemple, in laboratory condition, most of tested algorithms works very fine and having good performence because the  nature and the number of the input signals are almost known apriori and then the mixing process is well determined for the separation operation.  But in fact, the real-life scenario is much more different and of course the problem is becoming much more complicated due to the the fact of having the most of the parameters of the linear equation are unknown. In this paper, we present a novel method based on Gaussianity and Sparsity for signal separation algorithms where independent component analysis will be used. The Sparsity as a preprocessing step, then, as a final step, the Gaussianity based source separation block has been used to estimate the original sources. To validate our proposed method, the FPICA algorithm based on BSS technique has been used.

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